Applied Sparse regularization (L1), Weight decay regularization (L2), ElasticNet, GroupLasso and GroupSparseLasso to Neuronal Network.
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Updated
May 26, 2022 - Python
Applied Sparse regularization (L1), Weight decay regularization (L2), ElasticNet, GroupLasso and GroupSparseLasso to Neuronal Network.
All my Machine Learning Projects from A to Z in (Python & R)
Pre-Rendered Regularization Images fou use with fine-tuning, especially for the current implementation of "Dreambooth"
Code and Data sets for the EMNLP-2021-Findings Paper "ProtoInfoMax: Prototypical Networks with Mutual Information Maximization for Out-of-Domain Detection"
All about machine learning
Python source code for EMNLP 2020 Findings paper: "Domain Adversarial Fine-Tuning as an Effective Regularizer".
fdaPDE: Physics-Informed Spatial and Functional Data Analysis
This is Collection of Regularization Deep learning techniques with code and paper
A Julia package to perform Tikhonov regularization for small to moderate size problems.
Classification Using Logistic Regression by Making a Neural Network Model. This project also includes comparison of Model performance when different regularization techniques are used
Implementation of all basic algorithms needed in Deep Learning
Regularized Levenberg-Marquardt algorithm for nonlinear regression on small size datasets
Machine learning project for predicting movie ratings in Movielens data set. Naive with regularization method used. Created as a capstone project for Data Science HarvardX course.
This work attempts to generalize a stock forecasting neural network using Bayesian regularization so that predictions can be performed without an overfitted model, considering the highly volatile market these days.
A quantitative measure of disease progression one year after baseline
Machine Learning and Data Mining Projects (2022-2023)
Regularized maximum likelihood estimation for discrete choice models on the LPMC dataset
the implementation of a multilayer perceptron
Using encoder-decoder neural networks to learn representations of personal walking style, and generating person-specific gait for desired activities.
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